Every inpatient discharge represents a check that a healthcare provider writes itself, with inpatient coding serving as the pen. This simple statement doesn’t capture the complexity of assuring the pen is functioning optimally or the amount of the check is accurate. DRG variances caused by coding inaccuracy result in hundreds, to tens of thousands of dollars in unrealized revenue on an individual discharge. Extrapolated across all a provider’s inpatient discharges paid on DRG, this represents a significant financial red flag that cannot be ignored.
According to an AHIMA practice brief, 95% is the benchmark for coding accuracy that provider organizations should be striving for. Provider organizations come in all shapes and sizes, from large, multi-facility systems shaped by M&A activity, to community hospitals. Some exceed this benchmark and some struggle to attain it. But regardless of size or location, organizations have an accuracy gap to fill. This gap typically represents millions of dollars of unrealized revenue. Understanding the root causes i vital.
Healthcare providers deal with numerous challenges and competing priorities when trying to ensure coding and DRG accuracy:
- DNFB and coder productivity: Speed and accuracy are not complimentary. DNFB puts pressure on inpatient coders to abstract accounts quickly, often as the expense of accuracy. Productivity metrics can encourage behaviors that compromise accuracy.
- Resourcing: Resources are finite. Hospitals rightfully prioritize clinical investments over administrative. The consequence of this is that inpatient coding is expected to do more with the same amount of resources or in some cases, more with less. Demand for quality inpatient coders is high due to the advanced nature of the skill set. It can be difficult to recruit, retain, and train for this work.
- Technology limitations: Front-end coding technologies like CAC are becoming ubiquitous. And while these technologies certainly have their merits, they are not infallible. CAC sequencing errors are common and can have a significant impact on the DRG and reimbursement. Supporting technologies can also be slow to make updates associated with annual changes to standard coding practices.
- Documentation: Physicians can be inconsistent in the depth and breadth of the documentation they use to populate the record. Inpatient coders do not have the luxury of interpretation and must be judicious in their utilization of the retrospective query process, if one exists.
- Industry change: The transition from ICD -9 to ICD-10 represented a 10x increase in code volume. This explosion in complexity has a continued impact on coding and DRG accuracy, even several years after the transition.
- Opportunity cost: Investing human capital to increase coding accuracy often involves trade-offs. Experienced coders are often tapped as an internal auditing layer to provide education and accuracy assurance. Utilizing them in this capacity has its merits, but the backfill of less experienced resources can have a temporary downward effect on accuracy. Internal efforts are only as good as the methods used to determine the records selected for auditing.
Organizations that are the very best at addressing these challenges are the ones utilizing a multi-disciplinary approach, with a combination of both human and technology resources. Some elements of a successful approach to ensuring coding and DRG accuracy include:
- Education: It is important to first establish a culture of education. Help coders understand that education efforts are designed to support their development. Education programs should be separate from the employee evaluation process and not be perceived as punitive in nature. Identify areas of focus, leverage experienced team members as educators, and cascade relevant information broadly and repeatedly across the team. Education is a discipline, not an event.
- Collaboration: Remove the siloes that often define the clinical documentation functions. Ideally physicians, clinical documentation professionals, and inpatient coders should be working in concert. Establishing physician champion relationships and joint CDI/coding meetings to discuss trends are practical steps that can help reduce the silo effect.
- Shine light on assumptions: Understand the written and unwritten rules that influence how coding team’s function and pressure test their consistency with organizational goals. Know where coders deviate from industry standards and why. Is there a quality over reimbursement initiative in place? If so, make sure the standards associated with that initiative are widely understood across the various teams.
- Utilize safety net technologies: Front-end technologies such as CAC are common. End of process technologies to catch variances post-code complete are less common but can provide both additional reimbursement and valuable inputs into the education process.
Inpatient coding teams get it right most of the time. This can be easy to lose sight of given the impact of coding and DRG inaccuracy. Recognizing that fault does not reside solely with the coders themselves but is a consequence of the environment is an important first step to addressing the accuracy gap. Second, elicit feedback. Understand the specific challenges coders perceive as keeping them from optimizing accuracy. Third, plan for and implement a multi-pronged approach based on coder feedback and the recommendations made here. Organizations that invest appropriately to put their teams in a position be successful are more likely to reduce the accuracy gap and optimize reimbursement.